Data-scientific study of Kronecker coefficients
Fuente:
arXiv
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| Format: | Preprint |
| Published: |
2023
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| _version_ | 1866913532669329408 |
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| author | Lee, Kyu-Hwan |
| author_facet | Lee, Kyu-Hwan |
| contents | We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of partitions and use them to describe a sufficient condition for Kronecker coefficients to be nonzero. The results provide new methods and perspectives for the study of these coefficients. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2310_17906 |
| institution | arXiv |
| publishDate | 2023 |
| record_format | arxiv |
| spellingShingle | Data-scientific study of Kronecker coefficients Lee, Kyu-Hwan Representation Theory Combinatorics We take a data-scientific approach to study whether Kronecker coefficients are zero or not. Motivated by principal component analysis and kernel methods, we define loadings of partitions and use them to describe a sufficient condition for Kronecker coefficients to be nonzero. The results provide new methods and perspectives for the study of these coefficients. |
| title | Data-scientific study of Kronecker coefficients |
| topic | Representation Theory Combinatorics |
| url | https://arxiv.org/abs/2310.17906 |